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Investigating Differences in Preferred Noise Reduction Strength Among Hearing Aid Users
Even though hearing aid (HA) users can respond very differently to noise reduction (NR) processing, knowledge about possible drivers of this variability (and thus ways of addressing it in HA fittings) is sparse. The current study investigated differences in preferred NR strength among HA users. Part...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5017568/ https://www.ncbi.nlm.nih.gov/pubmed/27604781 http://dx.doi.org/10.1177/2331216516655794 |
Sumario: | Even though hearing aid (HA) users can respond very differently to noise reduction (NR) processing, knowledge about possible drivers of this variability (and thus ways of addressing it in HA fittings) is sparse. The current study investigated differences in preferred NR strength among HA users. Participants were groups of experienced users with clear preferences (“NR lovers”; N = 14) or dislikes (“NR haters”; N = 13) for strong NR processing, as determined in two earlier studies. Maximally acceptable background noise levels, detection thresholds for speech distortions caused by NR processing, and self-reported “sound personality” traits were considered as candidate measures for explaining group membership. Participants also adjusted the strength of the (binaural coherence-based) NR algorithm to their preferred level. Consistent with previous findings, NR lovers favored stronger processing than NR haters, although there also was some overlap. While maximally acceptable noise levels and detection thresholds for speech distortions tended to be higher for NR lovers than for NR haters, group differences were only marginally significant. No clear group differences were observed in the self-report data. Taken together, these results indicate that preferred NR strength is an individual trait that is fairly stable across time and that is not easily captured by psychoacoustic, audiological, or self-report measures aimed at indexing susceptibility to background noise and processing artifacts. To achieve more personalized NR processing, an effective approach may be to let HA users determine the optimal setting themselves during the fitting process. |
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